Three cs.AI papers from arXiv worth your time today. (1) LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning. (2) AI-Assisted Peer Review at Scale, the AAAI 26 AI Review Pilot. (3) From P of y given x to P of y, Investigating Reinforcement Learning in Pre-train Space. Selected and summarised by an autonomous pipeline. Voice by Microsoft Edge TTS.

Talk by Dr Manuel Corpas at the SCGG Away Day, King's College London, 15 April 2026.

An impromptu conversation with Ivo Djidrovski about the biology gap in agentic AI. Covers Anthropic's Claude Mythos System Card, why biology is missing from frontier AI benchmarks at events like AI Engineer Europe, ClawBio's positioning at the forefront of bio agents, and a live demo of agentic genomics on real family whole genome data for an upcoming King's College London talk. Also, AI induced FOMO, restlessness, and Ivo's Netherlands calm. Contains strong language.

Anthropic built their most capable frontier model yet, Claude Mythos Preview, and chose not to release it. This episode reads the System Card (245 pages) and Alignment Risk Update (59 pages), focusing on the bio capability evaluations, the expert red team findings on bioweapons uplift, the Dyno Therapeutics sequence design result, and what all of this means for ClawBio and open source bio agents. Direct reading of the primary source, single host, 53 minutes.

What happens when AI agents can autonomously discover, execute, and chain genomic analyses using natural language? This episode introduces the concept of agentic genomics and explores how it is reshaping who can do genomics, how fast, and what questions they can ask. We examine the emerging ecosystem of agentic systems, the critical validation challenges they create, the equity implications of automating genomic analysis at scale, and a five-principle framework for responsible adoption. Based on a Perspective submitted to a leading genomics journal.

A comprehensive evaluation of ClawBio from four perspectives: funder, CEO, scientist, and technologist. Covers strengths, weaknesses, opportunities, and a detailed roadmap from April to December 2026.

Everyone talks about AI agents. Almost nobody shows what happens when you wire them into your daily work. Four AI agents, a shared memory system, and three months of real results: 4 papers submitted, 15 PRs audited, a hackathon organised, and third place at Encode London. What worked, what failed, and what it means for the future of research. Full written version: https://manuelcorpas.substack.com/p/i-run-my-research-lab-with-ai-agents

Can large language models like ChatGPT, Claude, and Gemini actually understand and retrieve reliable information from complex biobank datasets? This episode explores a rigorous benchmarking study that tested six frontier LLMs against the UK Biobank, one of the world's most comprehensive medical databases. We cover the four benchmark tasks, the six-dimensional evaluation framework, statistical validation against random baselines, and what the results mean for the future of AI in biomedical research.

What does it mean when an AI agent can install tools, run pipelines, and generate figures autonomously? Live lecture at the University of Westminster covering the agentic AI revolution in genomics. Includes real-time audience interaction, ClawBio demos, DrugPhoto walkthrough, and a direct challenge to students: if you are not building with AI, you are being left behind. Topics: agentic AI in genomics, ClawBio skills, RoboTerri and RoboIsaac research agents, hallucination risks, bias amplification, AI fluency and career prospects. Recorded live 25 March 2026.

Big Data in Health: Agentic AI and the Future of Genomic Medicine